GROUNDED THEORYWilhelm A. S. Damsleth

2013-10-28 / INF5220 Guest Lecture

THE “AGENDA-SLIDE”

• Some theory

- What is GT?

- GT Pros&Cons

- GT Primer (“crash course”)

- Comments on codes

- Comments on sources

• Some static examples

• Some live examples!

Strauss, Anselm L. (1987)“Qualitative Analysis For Social Scientists”

(The book is 335 pages – that’s almost as many slides as I have in this presentation!)

GROUNDED THEORY IS

• A methodology and analytical approach for developing theory that is grounded in your data

• A generative process

• An oppurtunity

• An opposition to read-then-do-then-write (Crang & Cook, 2007)?

• What does Madden (2010) say?

• Grounded Theory is not journalism*

• Grounded Theory is not a quantitative analysis*

• Grounded Theory is not an excuse

GROUNDED THEORY IS NOT

* Grounded Theory –

Quantitative Journalism?

GT ANALYSIS: MAIN ELEMENTS

1. Concept-Indicator Model

2. Data Collection

3. Coding

4. Core Categories

5. Theoretical Sampling

6. Comparisons

7. Theoretical Saturation

8. Integration of the Theory

9. Theoretical Memos

10. Theoretical Sorting

(Strauss 1987, p. 23)

1. Concept-Indicator Model

2. Data Collection

3. Coding

4. Core Categories

5. Theoretical Sampling

6. Comparisons

7. Theoretical Saturation

8. Integration of the Theory

9. Theoretical Memos

10. Theoretical Sorting

Data collection (SSI’s)

Transcription

Open Coding

Axial Coding

GT PRIMER

Code Memos Theory

TRANSCRIBING

• Accurate and precise data forms the crucial base of GT analysis

• Accuracy – Nuances• “Transcribing sucks”

• Deal w/ it!• Use a good template

(you can have mine)

“My first fully transcribed interview”1:26:56 – 25 pages – 11.009 words… one of many.

OPEN CODING

• Analyze and assign codes to your data

• Use constructed codes or in vivo codes

• Coding paradigms (Strauss 1987, p. 27-28)• conditions• interaction among the actors• strategies and tactics• consequences

“Coding. The general term for conceptualizing data; thus, coding includes raising questions and giving provisional answers (hypotheses) about categories and about their relations. A code is the term for any product of this analysis (whether category or a relation between two or more categories).”

(Strauss 1987, p. 20)

(W. Damsleth, Master thesis, interview #7)

externalitythem-us

control

externalitydoes not fit me

misfit

inappropriatenessexternality

distancing

counter-tradition

control

self-defence

investment protection

constructed rigidity control

“ F r o m t h e s t a n d p o i n t o f t h e u s e r , o f c o u r s e ; b u t , t h e c h a l l e n g e i s : T h e r e a r e a l wa y s s u g g e s t i o n s c o m i n g i n f r o m u s e r s , s u b j e c t i v e l y , f r o m t h e u s e r : “ I wa n t i t t h i s wa y . ” A n d t h e n y o u h a v e a n o t h e r u s e r w h o wa n t s e x a c t l y t h e s a m e , b u t i n a n o t h e r wa y , a n d t h e n y o u h a v e a t h i r d u s e r t h a t wa n t s t h e s a m e b u t i n a t h i r d wa y . We h a v e o n e c o m m o n s y s t e m a n d t h a t ’ s w h y w e h a v e o n e wa y t o d o i t . ”

externality them-us

control

does not fit me

misfit

inappropriatenessdistancing

counter-tradition

self-defence

investment protection

constructed rigidity

Codes

Interview)7 Interview)8

Too#difficult 17 19

Avoiding#Microwork 11 11

Constructed#Rigidity 20 2

Control 19 3

Working#Around 9 13

Telephone 11 10

Manual#RouBnes 11 9

Not#my#job 11 9

TimeGconsuming 8 12

Competency 14 5

Manual#AutomaBzaBon 14 5

Competencial#inadequacy 6 11

Fails#to#Automate 8 8

Future#System 14 2

DetecBve#work 2 13

Faith#in#the#Construct 13 2

Backstage,#No#Knowledge#of 11 3

Bad#UI 9 5

Compliance 7 7

ERP#System#by#Name 12 1

(W. Damsleth, Master thesis, Methods chapter)

Codes#in#use References#coded

Interview#7 69 434

Interview#8 89 369

Total 803

• Coding is highly personal!

• Coding paradigms (Strauss 1987, p. 27-28)• conditions• interaction among the actors• strategies and tactics• consequences

AXIAL CODING(“GROUPING” OR “CATEGORIZING” ALONG DIMENSIONS)

• Group codes into categories that have axial variability represented in the codes

“Dimensionalizing. A basic operation of making distinctions, whose products are dimensions and sub dimensions.

Category. since any distinction comes from dimensionalizing, those distinctions will lead to categories.”

(Strauss 1987, p. 21)

colleaguecomputer system developer nearness

upper managementACBD

irrelevantcomputer system relevance for my job

highly relevantAC B D

E

E

Relationship! – Are computer systems developed by colleagues perceived as more relevant in the users job than those from upper management?

New!

MEMOING AND ANALYSIS

• When discovering a relationship between concepts (codes), categories and dimensions – write a memo!

• Code Memos are linked to one or several codes, categories or relationships

• Write Code Memos immediately when the idea(s) strike(s) you! Do NOT wait – the idea is fleeting, your data is not!

• Code Memos – or paper to publish? No form requirement – only structure required!

Continuous analysis

Continuous tuning

Working around

ControlExternality

Not my job Can’t keep track

Does not fit me

Duplicate records

“Cheating”

Misfit

Inappropriateness

Insecurity

[Feeling of] Fit

Counter-tradition

Unshame

Without consequence

Constructed Rigidity

INTEGRATIVE DIAGRAMS

PROGRAMMATIC ANALYSIS

Weak or no correlation

Strong correlation

QUICK COMMENTS ON CODES

• Micro-coding

• Macro-coding

• Ten codes, a million codes?

• “Let the codes come to me and do not forbid them, for the Grounded Theory belongs to such as these!”

• It's easy to keep using the same codes – and dangerous

• Remember axial coding!

MORE QUICK COMMENTS ON CODES

• Codes will crystalize while coding.

• What happens to new codes you discover while coding? Should you go back and re-code the rest of the data in this light? Again? And again?

• Keep going until the theory is saturated!

• You will get successively more codes with higher granularity as you code

• Go back? When is enough?

Do not group the codes too early!

One occurrence of a particular code can be ten times as meaningful as ten occurrences of another code

and

ON SOURCES

ON SOURCESGreat Sources Good Sources Challenging Sources Poor Sources

Interviews– transcribed! Routine descriptions Participatory/Passive

Observation Interview notes

More interviews– go back! Job descriptions Video Abridged interviews

Academic texts Internal documents, policy documents Focus groups

Other unprepared texts Prepared statements

Source code Press releases, journalist work

Objectivity and Accuracy

Suita

bility

for G

T an

alysis

What about quantitative data?

You can use it – to support or contradict your findings!

GT PRO & CONPro Con

(Usually) Great results! Takes a lot of time

Grounded Data Takes a lot of work

The discovery of more than the sum of your data Can give false trails

Free styled, suitable for many sorts of outputs Can’t use all your results

Combines well with many other methodologies Needs immersion

You don’t need to know for sure what you’re looking for You can’t know for sure what you’re looking for

Demonstration time!

Wilhelm A. S. Damsleth

KEEPCALMAND

CODEON

10/29/12 7:32 PM

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Wilhelm A. S. Damsleth